Oven Dryness Research Articles

Effects of tire wear particles on the water retention of soils with different textures in the full moisture range

Tire wear particles (TWPs) are significant contributors to microplastic pollution in the environment, yet there is limited scientific information concerning their impact on soil hydraulic properties. This study aimed to investigate the impact of TWPs at different concentrations (1, 4, 8, and 16% of the air-dried mass of packed soil samples, w/w) on the water retention curves (WRC) of southern California soils with five different textures (clay, clay loam, silt loam, sandy loam, and loamy sand). The concentrations of 8% and 16% were selected to represent extreme pollution scenarios that might occur near highway corridors. High-resolution water retention data, spanning from saturation to oven dryness, were generated using HYPROP™ and WP4C dew point meter instruments. We also developed WRC scaling equations based on the quantity of TWPs. The bulk density of the samples decreased as the TWP concentration in soils increased. The inclusion of very high concentrations of TWPs (8% and 16% w/w) led to a significant reduction in soil moisture content in the intermediate and dry ranges across various soil textures. However, at the same moisture range, adding 1% TWPs had a minimal impact on soil moisture reduction, while the influence of the 4% TWPs concentration treatment was noticeable only in loamy sand and partially in clay loam soils. Additionally, the overall plant available water decreased with increasing TWP concentrations, except for the clay soil. The texture-specific scaling models exhibited promising performance, with RMSE values ranging from 0.0061 to 0.0120 cm3 cm−3. When bulk density was included as an additional input predictor to construct a single scaling model for all textures, the RMSE increased. Nevertheless, it still indicated a good fit ranging from 0.007 to 0.024 cm3 cm−3, highlighting the suitability of simple scaling for identifying WRC in TWPs-polluted soils, particularly for practical purposes. The findings of this study can contribute to a better understanding and quantification of the impact of TWPs on soil hydrology.

A Novel Three-Segment Model to Describe the Entire Soil–Water Characteristic Curve

This study aims to accurately describe the soil–water characteristic curve (SWCC) across the full range from saturation to oven dryness. We propose a smooth, continuous three-segmented SWCC model that divides the saturation range into wet, air-dried, and oven-dried segments. The two model junction points are anchored at matric suctions of 104.5 and 106.5 cm, respectively. The soil water content at 104.5 cm represents the maximum soil hygroscopy, reflecting the maximum water content in air-dried soil, while the soil water content at 106.5 cm characterizes the minimum soil water content. This imbues the junction points with specific physical significance regarding soil moisture content and matric potential. The model was tested with the water retention data of nine soils across the SWCC and compared with three existing SWCC models based on the adjusted coefficient of determination (adjR2) and root mean square error (RMSE). The results indicated that the proposed model accurately described the entire SWCC. The three-segmented model yielded an adjR2 of >0.99 and an RMSE of ≤0.022 cm3 cm−3, outperforming other models. We also introduce a new method for predicting soil water data in air-dried and oven-dried segments. The results showed that the predicted soil water content values were accurate.

Metropolis-Hastings Markov Chain Monte Carlo Approach to Simulate van Genuchten Model Parameters for Soil Water Retention Curve

The soil water retention curve (SWRC) is essential for assessing water flow and solute transport in unsaturated media. The van Genuchten (VG) model is widely used to describe the SWRC; however, estimation of its effective hydraulic parameters is often prone to error, especially when data exist for only a limited range of matric potential. We developed a Metropolis-Hastings algorithm of the Markov chain Monte Carlo (MH-MCMC) approach using R to estimate VG parameters, which produces a numerical estimate of the joint posterior distribution of model parameters, including fully-quantified uncertainties. When VG model parameters were obtained using complete range of soil water content (SWC) data (i.e., from saturation to oven dryness), the MH-MCMC approach returned similar accuracy as the widely used non-linear curve-fitting program RETC (RETention Curve), but avoiding non-convergence issues. When VG model parameters were obtained using 5 SWC data measured at matric potential of around −60, −100, −200, −500, and −15,000 cm, the MH-MCMC approach was more robust than the RETC program. The performance of MH-MCMC are generally good (R2 > 0.95) for all 8 soils, whereas the RETC underperformed for coarse-textured soils. The MH-MCMC approach was used to obtain VG model parameters for all 1871 soils in the National Cooperative Soil Characterization dataset with SWC measured at matric potentials of −60 cm, −100 cm, −330 cm, and −15,000 cm; the results showed that the simulated SWC by MH-MCMC model were highly consistent with the measured SWC at corresponding matric potential. Altogether, our new MH-MCMC approach to solving the VG model is more robust to limited coverage of soil matric potential when compared to the RETC procedures, making it an effective alternative to traditional water retention solvers. We developed an MH-MCMC code in R for solving VG model parameters, which can be found at the GitHub repository.

Development of a New Pedotransfer Function Addressing Limitations in Soil Hydraulic Models and Observations

AbstractThe most applied pedotransfer functions (PTFs) often suffer from two main limitations: (a) the soil hydraulic models (SHMs) only account for capillary forces and/or the models show an unrealistic decrease near saturation for fine‐textured soils; (b) the observations of soil hydraulic properties (SHPs) used to generate the PTF generally do not cover very dry conditions. In this paper, we first present a simple method for predicting SHPs in the dry range from soil texture information. Together with measurements that cover only a relatively high matric potential range, the method yielded a good prediction of the complete SHPs from saturation to oven dryness. With this method, we extended a public dataset to cover dry conditions, and then applied it to develop a new PTF for a SHM that accounts for both capillary and adsorption forces and overcomes the unrealistic decrease near saturation for fine‐textured soils. A comparison with other PTF that was developed for the capillary‐based soil hydraulic model showed that the new PTF provided the most accurate predictions of SHPs. It reduced the root‐mean‐square‐error value from 0.055 to 0.045 cm3 cm−3 in predicting water content and from 0.84 to 0.66 log10 (cm d−1) in predicting hydraulic conductivity. We further applied this method to extend an existing capillary‐based PTF to dry conditions. The results showed an improved performance, with reported RMSE reduced from 0.058 (original) to 0.056 (extended) cm3 cm−3 and from 1.43 (original) to 1.20 (extended) log10 (cm d−1) for prediction of water content and hydraulic conductivity, respectively.

A New Fractal Approach to Account for Capillary and Adsorption Phenomena in the Water Retention and Transfer Properties of Unsaturated Soils

AbstractTo describe the water retention and transfer properties of an unsaturated soil over the whole range of matric suction, it is necessary to account for both capillary and adsorption phenomena. Existing models combine well‐known empirical functions for capillary water at lower suctions and more physically based ones for adsorptive water at higher suctions. To determine their full set of parameters, they however require different optimization procedures, among which those coming from capillary models are empirical. In this context, the main objective of this work is to develop a simple and robust physically based model of the water retention and transfer properties of unsaturated soils valid from saturation to oven dryness. To do so, new capillary‐based water retention and hydraulic conductivity functions founded on the fractal approach have been derived from the pore size distribution, by means of the Young‐Laplace law and Mualem's model. To describe adsorption phenomena, these functions are combined with those used in the Peters‐Iden‐Durner (PID) model, providing a model along the full range of suctions, with less parameters than the existing models. Our work also shows that some parameters are directly determined from the experimental grain size distribution data (the fractal dimension), or from the water retention data (air entry suction and residual water content), leaving only two parameters to be optimized. The model was successfully validated with respect to published experimental data from 10 different coarse, sandy, and clayey soils.

Simple functions for describing soil water retention and the unsaturated hydraulic conductivity from saturation to complete dryness

Many applications require accurate soil hydraulic functions that can describe the dynamics of water in variably saturated systems from full saturation to complete dryness. Current functions considering zero water content at the dry end involve the summation of capillary and adsorption functions. This study proposes relatively simple yet complete soil hydraulic functions from full saturation to oven dryness that can be incorporated into existing models. The proposed water retention model is constructed by scaling the saturation function of Fredlund and Xing (1994) to describe capillary and adsorptive water retention as well as zero water content at oven dryness. To describe the hydraulic conductivity due to capillary and film flow, the model of Wang et al. (2018) is used. We further incorporated hysteresis in the water retention function of Wang et al. (2018). Testing on 241 hydraulic property data sets covering a wide range of soil textures from sands to clays, shows good agreement with laboratory observations, especially for coarse-textured soils. The proposed model accounts for the following processes: hysteretic capillary and adsorptive water retention, hysteretic hydraulic conductivity as a function of pressure head, non-hysteretic hydraulic conductivity as a function of water content, the effects of entrapped air, and closed scanning curves. This paper successfully derives the parameters of the main wetting curve from the main drying curve. Using the proposed functions for soil water flow modelling should lead to improved dynamic flow predictions, especially for drying soil conditions.

Studying Unimodal, Bimodal, PDI and Bimodal-PDI Variants of Multiple Soil Water Retention Models: I. Direct Model Fit Using the Extended Evaporation and Dewpoint Methods

This study focuses on the reliable parametrization of the full Soil Water Retention Curve (SWRC) from saturation to oven-dryness using high resolution but limited range measured water retention data by the Hydraulic Property Analyzer (HYPROP) system. We studied the performance of five unimodal water retention models including the Brooks and Corey model (BC model), the Fredlund and Xing model (FX model), the Kosugi model (K model), the van Genuchten constrained model with four free parameters (VG model), and the van Genuchten unconstrained model with five free parameters (VGm model). In addition, eleven alternative expressions including Peters–Durner–Iden (PDI), bimodal, and bimodal-PDI variants of the original models were evaluated. We used a data set consisting of 94 soil samples from Turkey and the United States with high-resolution measured data (a total of 9264 measured water retention data pairs) mainly via the HYPROP system and supplemented for some samples with measured dry-end data using the WP4C instrument. Among unimodal expressions, the FX and the K models with the Mean Absolute Error (MAE) values equal to 0.005 cm3 cm−3 and 0.015 cm3 cm−3 have the highest and the lowest accuracy, respectively. Overall, the alternative variants provided a better fit than the unimodal expressions. The unimodal models, except for the FX model, fail to provide reliable dry-end estimations using HYPROP data (average MAE: 0.041 cm3 cm−3, average r: 0.52). Our results suggested that only models that account for the zero water content at the oven dryness and properly shift from the middle range to dry-end (i.e., the FX model and PDI variants) can adequately represent the full SWRC using typical data obtained via the HYPROP system.

A novel segmental model to describe the complete soil water retention curve from saturation to oven dryness

Traditional water retention models that use the residual water content parameter fail to accurately describe the dry end of the soil water retention curve (SWRC). We developed two- and three-segment smooth, continuous SWRC models, acknowledging the existence of three saturation states, for water contents ranging from saturation to oven-dryness. The equations near the oven dryness end in both models were obtained based on the assumption of proportionality between the soil water content and the logarithm of suction. The equations in the wet range for both models were modified from the van Genuchten model and/or Brook-Corey model(s) by removing the residual water content parameter. The continuity and smoothness conditions at the junction points reduced the fitting parameters of the three- and two- segment models from 9 to 4 and from 6 to 3, respectively. Both models were tested with water retention data from the Washington soil database and the Unsaturated Soil Hydraulic Database (UNSODA) over nearly the entire range. Both models were also compared with seven existing SWRC models and were evaluated on the basis of the adjusted coefficient of determination (adj R2), the root mean square error (RMSE) and the Kashyap information criteria (KIC). The testing results showed that the three-segment model performed better than the two-segment model at fitting the SWRC at the dry end. For the three-segment model, the adj R2 value was greater than 0.90, the RMSE was less than 0.02, and the mean KIC value was −67.0, and these values were superior to those of the other models. In addition, the three-segment model was robust and stable for extrapolation of values in the dry range when data near the dry end were unavailable.

An empirical soil water retention model based on probability laws for pore‐size distribution

ABSTRACTKnowledge of the soil water retention curve (SWRC) is critical to mathematical modeling of soil water dynamics in the vadose zone. Traditional SWRC models were developed based on bundles of cylindrical capillaries (BCCs) using a residual water content, which fail to accurately describe the dry end of the curve. This study improved and expanded on the traditional BCC models. Specifically, the total water retention was treated as a weighed superposition of capillary and adsorptive components. We proposed a mathematical continuous expression for water retention from saturation to oven dryness, which also allowed for a partition of capillary and adsorptive retention. We further evaluated six capillary retention functions using different probability laws for pore‐size distribution—namely, the log‐logistic, Weibull, lognormal, two‐parameter van Genuchten (VG), three‐parameter VG (or Dagum), and Fredlund–Xing (FX) distributions. Model testing against 144 experimental data showed better agreement of the proposed model with experimental observations than the traditional approaches that use the residual water content. The Dagum and FX distributions, which have one more degree of freedom, provided better agreement with experimental data than the other four distributions. The log‐logistic and lognormal distributions fitted the experimental data better than the Weibull and VG distribution for loam soils. In addition, the fitted weighting factor w using the log‐logistic and lognormal distributions better correlated to soil clay content than the other four distributions. Our study suggests that the log‐logistic and lognormal distributions are more suitable to model soils’ pore‐size distribution than other tested distributions.

Comparison of the performance of 22 models describing soil water retention curves from saturation to oven dryness

AbstractSoil water retention curve (SWRC) is key hydraulic property for vadose zone hydrology. Selected 22 SWRC models with different structures were divided into four types: traditional, single‐segment, two‐segment, and three‐segment models. According to the accuracy and model selection criterion, these models were compared and evaluated using water retention data from saturation to oven dryness of 94 soil samples covering almost all soil types. Among the models, the EG model (exponential model combined with the Groenevelt–Grant model) shows the best performance, but the BC (Brooks–Corey) and VG (van Genuchten) models performed the worst. The relationship between model performance and complexity showed that traditional models with residual water content performed worse than segmental models from saturation to oven dryness, and the segmental models performed worse with an increase in the segment number. In general, models with more parameters perform better, but when the parameter number is greater than five, the model performance gradually worsens due to the equifinality of different parameters. The correlation analysis between soil properties on model performance showed that soil texture has a more significant effect on model performance than bulk density and organic matter content, because the models are primarily affected by their mathematical forms rather than the physical significance of the parameters. Each model picks its limitations and may apply to only one or particular group(s) of soil(s). Therefore, the complementarities of different models may be a great choice to improve SWRC fitting and simulation in arid soil.

Comparison of different approaches for estimating soil water characteristic curves from saturation to oven dryness

Three approaches were compared for estimating continuous soil water characteristic curves (SWCCs) from easily accessible soil properties. The approaches included combining the Mohammadi and Vanclooster (2011) method (the MV method) with the van Genuchten (1980) model (MV-vG approach), the modified MV-vG approach, and combining the Jensen et al. (2015) method with the Fredlund and Xing (1994) model (the J-FX approach). A total of 195 disturbed soil samples and 195 undisturbed soil cores were collected from 1-m soil profiles in an arid region of northwestern China. Particle size distribution (PSD) and organic matter (OM) content were determined. The volumetric water content and matric potential data pairs of each sample during the drying process were measured using a high speed centrifuge. All of the measured soil properties were used to evaluate the applicability of the approaches for continuous SWCC estimation. The MV method has a robust physical basis and is independent of any experimental SWCC data pairs. Some intrinsic shortcomings affect the estimation of continuous SWCC by the MV-vG approach. The integration of a soil structure feature improved the estimation of the modified MV-vG approach. The estimation of the J-FX approach for SWCC is robust for the five textural classes, and outperformed the MV-vG approach and the modified MV-vG approach. The good performance of the J-FX approach can be attributed in part to the fact that it distinguishes the dominant forces governing water retention of dry and wet ranges, and relates the PSD, specific surface area, and OM content to the pore size distribution. All these factors are vital for soil water retention, but have been simplified or ignored by the MV method. Both the modified MV-vG approach and the J-FX approach are promising for estimating continuous SWCCs at a regional scale. The modified MV-vG approach may be suitable for rigid soils with medium textures at potentials above wilting point. The J-FX approach is applicable for the whole range of water retention from saturation to oven dryness for soils with substantially varying bulk density, soil texture and organic matter content at a regional scale. The results of this study are fundamental for use in simulating the transfer of water and solutes in layered-structured soil profiles and for estimating the vegetation carrying capacity of soil available water in arid regions.

A Simple and Improved Model for Describing Soil Hydraulic Properties from Saturation to Oven Dryness

Core Ideas Soil hydraulic properties from saturation to oven dryness are needed to simulate soil water movement. A new soil hydraulic model was compared with the classic van Genuchten–Mualem models. The new model with different fitted parameters was more efficient than the van Genuchten–Mualem models. Soil water retention characteristics and hydraulic conductivity from saturation to oven dryness are needed for simulating soil water movement and solute transport, especially in arid and semiarid regions. The aim of this study was to derive a new soil hydraulic model and compare this model with the classic van Genuchten–Mualem (VGM) models (M1). A total of 12 soils with varying basic properties were selected from the Unsaturated Soil Hydraulic Database (UNSODA) for the evaluation of the new model. Five pairs of soil hydraulic models were considered, including M1 and the new model with different parameters fitted (M2–M5). Correlation analysis was conducted to analyze the relationships between the new model parameters and basic soil properties. In addition, the Morris method was applied to quantify the parameter sensitivity of the new model. Results showed that M2 to M5 gave slightly better performance than M1 in predicting soil water retention characteristics, with a decrease of ∼15% in the root mean squared error (RMSE). However, they produced substantially better performance than M1 in estimating soil hydraulic conductivities, with a decrease of ∼40% in the RMSE. The new model with all of the model parameters being fitted (M2) was more efficient than those with one or two model parameters not fitted. However, an over‐parameterization problem was detected with M2. Physically unrealistic parameters (e.g., the saturated soil water content and effective grain diameter) exist in M2. These parameters were found to have important influences on the results of the soil hydraulic properties prediction based on the Morris‐based sensitivity analysis. Overall, the new model with two parameters not fitted (M5) can best describe the soil hydraulic properties from saturation to oven dryness and had the potential to simulate water and solute transport in the vadose zone.

Effects of Bentonite, Hydrogel and Biochar Amendments on Soil Hydraulic Properties from Saturation to Oven Dryness

Effects of hydrogel, bentonite, and biochar as soil amendments on soil hydraulic properties and improving water availability from saturation to oven dryness were investigated. Soils were mixed with hydrogel (0.10%, 0.25%, and 0.50%), bentonite (0.5%, 1.0%, and 2.5%), and biochar (1.0%, 2.5%, and 5.0%) as soil amendments (weight:weight). Three methods (extended multistep outflow (XMSO), evaporation (EVA), and WP4 dewpoint potentiometer) were used to measure soil hydraulic properties from saturation to oven dryness. The cumulative XMSO results were more uniform across all the applied pressure steps for the amended soils. The EVA exhibited a shorter linear decrease during the first evaporation stage and a lower evaporation rate during the second evaporation stage. The WP4 results also exhibited that soil amendments increased the soil water content of the amended soils at low matric potentials. The results of soil water retention curves revealed that the unamended soil retained less water at any matric potential compared to the amended soils. Soil hydraulic conductivity decreased with increasing amount of soil amendments. The saturated hydraulic conductivity was higher for the unamended soil than the soils amended with 2.5% bentonite, 0.50% hydrogel, and 5.0% biochar by 11, 3, and 18 times, respectively. These results suggested that soil amendments improved soil water retentivity, which confirmed the appropriateness of these soil amendments for potential use in sandy soil improvements. However, field experiments and economical perception studies should be considered for further investigation.

Water Retention and Preferential States of Soil Moisture in a Cultivated Vertisol

Core Ideas Water retention data from saturation to oven dryness were collected for a Vertisol. New water retention and differential water capacity models were developed. Draining of intra‐aggregate pore space triggers the dry field soil moisture state. Mode of the textural pore space controls shift to wet field soil moisture state. Vertisols are well suited for rainfed agriculture in water‐limited environments as a result of their unique water transfer and retention characteristics. Despite their importance, the agro‐hydrological behavior of these soils under seasonally dry climates is not yet fully understood. We collected water retention data for a Vertisol, measured from saturation to oven dryness on 27 undisturbed topsoil (0–0.05 m) samples from an experimental field in south‐central Spain and related this information to the occurrence of field‐observed preferential soil moisture states. A continuous function was fitted to the mean gravimetric water retention data, Θ, consisting of the sum of a double exponential model and the Groenevelt and Grant model. An inflection point at pressure head |h| = 1.1 × 105 cm, Θ = 0.12 kg kg−1, and an equivalent pore radius, δ = 14 nm, was interpreted as the boundary between the clay inter‐ and intra‐aggregate pore spaces, corresponding with the transition from the intermediate to the dry field soil moisture state. The mode of the textural pore space (|h| = 7.3 × 103 cm, Θ = 0.21 kg kg−1, and δ = 200 nm) matched the transition from the wet to the intermediate field soil moisture state. We related these characteristics of the soil water retention curve with the spatiotemporal soil moisture dynamics and patterns observed in the field, characterized by fast transitions between preferential soil moisture states. The proposed framework is suitable for comparing the effects of different soil management strategies on the agro‐hydrological performance of Vertisols.

A mathematically continuous model for describing the hydraulic properties of unsaturated porous media over the entire range of matric suctions

Recent studies suggest that water flow in unsaturated porous media extends beyond the commonly known capillary-driven regime into the film regime. There is a need to develop the unsaturated hydraulic properties over the entire range of matric suctions to capture both flow regimes. In this study, Fredlund and Xing model is modified to represent the soil water retention curve from saturation to oven dryness. The new function is mathematically differentiable. The hydraulic conductivity function is composed of the capillary-driven term and film associated term, which is easy to apply. The new model has capacity to represent the bimodal hydraulic properties that are often present in structured and aggregated soils. Testing with the published data of sixteen soils shows good performance for both the water retention curve and the hydraulic conductivity function. For most soils, the new model results in a better agreement with observations than a published model. The result also indicates a possibility to improve the previously published film-associated hydraulic conductivity function.

Extrapolative capability of two models that estimating soil water retention curve between saturation and oven dryness.

Accurate estimation of soil water retention curve (SWRC) at the dry region is required to describe the relation between soil water content and matric suction from saturation to oven dryness. In this study, the extrapolative capability of two models for predicting the complete SWRC from limited ranges of soil water retention data was evaluated. When the model parameters were obtained from SWRC data in the 0–1500 kPa range, the FX model (Fredlund and Xing, 1994) estimations agreed well with measurements from saturation to oven dryness with RMSEs less than 0.01. The GG model (Groenevelt and Grant, 2004) produced larger errors at the dry region, with significantly larger RMSEs and MEs than the FX model. Further evaluations indicated that when SWRC measurements in the 0–100 kPa suction range was applied for model establishment, the FX model was capable of producing acceptable SWRCs across the entire water content range. For a higher accuracy, the FX model requires soil water retention data at least in the 0- to 300-kPa range to extend the SWRC to oven dryness. Comparing with the Khlosi et al. (2006) model, which requires measurements in the 0–500 kPa range to reproduce the complete SWRCs, the FX model has the advantage of requiring less SWRC measurements. Thus the FX modeling approach has the potential to eliminate the processes for measuring soil water retention in the dry range.

Review of Soil Water Retention Characteristic (SWRC) Models between Saturation and Oven Dryness

Soil water retention characteristic is the key soil property used in many applications in the fields of irrigation, hydrology, geotechnical engineering and soil science in general. Since the advent of digital soil mapping and digital soil assessment paradigms, there has been an upsurge of development of soil inference models and the need to increase accurate application of soil mapping products. All soils can be partially saturated with water and also near oven dryness. Therefore, constitutive models for soils should ideally represent the soil behaviour over entire range. This paper reviewed commonly used SWRC models. In order to stem potential for biasness, the models were grouped into three categories depending on the number of fitting parameters, namely, five-parameter, four-parameter and three-parameter categories. The evaluation used correlation and residual standard error statistics to choose the best overall performing model and in each category. Its results serve as a guide for selecting the models to be preferred for fitting SWRC in case there are limitations to the number of suction potential levels in the measured data.

Performance evaluation of models describing sorption isotherm in cementitious materials between saturation and oven dryness

The objective of this work is to evaluate nine closed-form analytical expressions that describe the sorption isotherm across the complete range of water contents for cementitious materials.To meet this objective, the models were compared in terms of their accuracy root mean square error (RMSE), linearity (coefficient of determination, R2, and adjusted coefficient of determination, Radj2), and prediction potential. Experimental data from controlled drying experiments performed on four cementitious materials were used for the model comparisons. All tested models were found to propose relatively realistic fits, and to have similar performances when tested on different types of materials except for cement paste with lower water to cement ratio.Models involving a large number of parameters do not significantly perform better than more simple ones, especially when one account for extra cost in terms of robustness implied by additional parameters.Overall, the Kosugi model based on a lognormal pore size distribution appears to be the best compromise between goodness of fit and number of parameters to estimate.

Evaluation of Three Models that Describe Soil Water Retention Curves from Saturation to Oven Dryness

Measuring a soil water retention curve (SWRC) with the pressure plate device is generally limited to matric suctions ≤1500 kPa. A few models have been proposed to describe the SWRC from saturation to oven dryness using measurements in the pressure plate matric suction range. The development and validation of these models were mostly based on a limited set of published measurements, and in general, the models have not been validated by independent data from additional soils. In this study, we tested the hypothesis that these models were able to predict the complete SWRC from a limited range of water retention data or by using water retention parameters available from the literature. Soil water retention measurements from saturation to oven dryness were conducted on disturbed, repacked soil samples of various textures using the pressure plate method and the dew point potential technique. When the model parameters were obtained from water retention data in the 0 to 1500 kPa range, the RMSE of water content was approximately 0.01. The RMSE of the Fayer–Simmons model was slightly larger than that of the Webb model and Khlosi model. In addition, the Fayer–Simmons model was sensitive to the data point near the matric suction of 1500 kPa. The Khlosi model produced acceptable results if data sets from 0 to 500 kPa were used for model establishment; larger errors were observed on some soils if the measured data were limited to the 0‐ to 100‐kPa range. All three models could provide reliable results across the entire range of soil water content if measurements in the 0‐ to 1500‐kPa range were available.

Cokriging Spatial Interpolation of Soil Water Dependent Repellency Parameters Determined with Two Different Tests

The nonlinear behavior of water repellency (WR) with respect to soil water content (θg) may be described by curve parameters derived from two widespread methodologies such as the water drop penetration time (WDPT) and molarity of an ethanol droplet (MED) tests. While the former measures WR persistence in terms of the infiltration time of a water drop sitting on the soil surface, the latter quantifies the repellency degree as contact angle or 90° surface tension, γ90° From a hydrologic point of view, the WDPT test may be considered more closely related to the natural infiltration process of the soil, but the infiltration times become prohibitively large (on the order of hours) in highly repellent soils; thus, the MED test is more convenient. This study was conducted to determine whether the spatial interpolation of time‐consuming WDPT measurements may be complemented with less time‐demanding WR parameters derived from the MED test. Measurements from saturation to oven dryness using both MED and WDPT were performed on 140 topsoil samples from a humid evergreen forest watershed of the Garajonay National Park (Canary Islands). We found useful links between curve parameters derived from the MED and WDPT tests. The area below the WR–θg curve measured with the WDPT test (SWDPT) was found to be correlated with that measured with the MED test (SMED) and with the θg at which repellency is triggered (θg‐min). By contrast, previously published relations that established a logarithmic relationship between 1/WDPT and γ90° were valid only in the dry soil state, but must be ruled out if soil water content is taken into account. We took advantage of the existence of such parameter correlations to show how cokriging geostatistical tools may be applied to improve the spatial interpolation of SWDPT, with SMED or θg‐min as subsidiary variables. In general, cokriging was superior to kriging in terms of mean variance minimization with little extra labor cost. A minimal‐effort spatial sampling strategy may be designed taking into account these considerations.